Slope One Recommendation Algorithm Through Combining Integrated Diffusion on Tripartite Graph

WANG Ran; XU Yi; HE Ming-hui; HU Shan-zhong

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Slope One Recommendation Algorithm Through Combining Integrated Diffusion on Tripartite Graph

更新时间：2026-09-04

- Slope One Recommendation Algorithm Through Combining Integrated Diffusion on Tripartite Graph
- Vol. 35, Issue 4, Pages: 6-11(2018)
- 作者机构：
  
  1. 安徽大学计算机科学与技术学院,安徽,合肥,230601
  2. 安徽大学计算智能与信号处理教育部重点实验室机构,安徽,合肥,230039
- 作者简介：
- 基金信息：
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- Published：2018
- 稿件说明：
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王冉, 徐怡, 何明慧, 胡善忠. 结合三部图综合扩散的Slope One推荐算法[J]. 微电子学与计算机, 2018, 35(4): 6-11.

WANG Ran, XU Yi, HE Ming-hui, et al. Slope One Recommendation Algorithm Through Combining Integrated Diffusion on Tripartite Graph[J]. 2018, 35(4): 6-11.
王冉, 徐怡, 何明慧, 胡善忠. 结合三部图综合扩散的Slope One推荐算法[J]. 微电子学与计算机, 2018, 35(4): 6-11. DOI：

WANG Ran, XU Yi, HE Ming-hui, et al. Slope One Recommendation Algorithm Through Combining Integrated Diffusion on Tripartite Graph[J]. 2018, 35(4): 6-11. DOI：

摘要

Slope One算法在评分预测时没有考虑项目之间的推荐关系

导致推荐的准确性和多样性不高

故提出了一种结合三部图综合扩散的Slope One算法.首先在三部图中加入了项目类别节点

然后利用三部图综合扩散计算项目之间的推荐度

最后利用得到的推荐度结合Slope One进行评分预测

由于三部图综合扩散算法同时经过用户节点和项目类别节点进行扩散

并且计算得到的项目之间的推荐度是非对称的

更能体现用户兴趣.本文在MovieLens数据集上利用4种评价指标进行5-折交叉验证.实验结果表明: 算法有效的提高了预测的准确度和多样性.

Abstract

The Slope One algorithm does not consider the recommended level between items when predict ratings

so the accuracy and diversity are not high. Therefore

a Slope One algorithm through combining integrated diffusion on tripartite graph is proposed. The idea is to add the genre nodes into the tripartite graph

and calculate the Slope One prediction ratings with the recommended level that calculated by the tripartite graph integrated diffusion algorithm. Since the diffusion through user nodes and item nodes

and the recommended level between the items is asymmetric

so it is better to reflect the user interest. The proposed method was tested by 5-fold cross-validation with four metrics

and the experiments on the MovieLens show that our approach achieves great improvement of prediction accuracy and diversity.

关键词

Keywords

references

李桃迎, 李墨, 李鹏辉. 基于加权Slope one的协同过滤个性化推荐算法[J]. 计算机应用研究, 2017, 34 (8) : 2264-2268. DOI: 2264

Shang M S, Zhang Z K, Zhou T, et al. Collaborative filtering with diffusion-based similarity on tripartite graphs[J]. Physica A Statistical Mechanics % Its Applications, 2009, 389(6): 1259-1264. DOI: 1259

孟祥武, 刘树栋, 张玉洁, 等. 社会化推荐系统研究[J]. 软件学报, 2015, 25(6): 1356-1372. DOI: 1356

张怡文, 王冉, 程家兴. 基于用户兴趣度的改进二部图随机游走推荐方法[J]. 计算机应用与软件, 2015, 31(6): 76-79. DOI: 76

Zhao Zhengde, Li Jianjun. Based on slope-one hybrid recommendation[C]// Advanced Research and Technology in Industry Applications. Ottawa, Ontario, IEEE, 2014: 203-205.

卢露, 魏登月. 一种基于隐语义模型的协同过滤算法[J]. 微电子学与计算机, 2015, 32(2): 73-75. DOI: 73

黄兰, 钱育蓉, 于炯, 等. 融合可信度和时效标签的商品推荐算法[J]. 微电子学与计算机, 2017, 34(6): 78-83. DOI: 78

杜茂康, 刘苗, 李韶华, 等. 基于邻近项目的Slope One协同过滤算法[J]. 重庆邮电大学学报(自然科学版), 2014, 26(3): 421-426. DOI: 421

廖志芳, 李玲, 刘丽敏, 等. 三部图张量分解标签推荐算法[J]. 计算机学报, 2012, 35(12): 2625-2632. DOI: 2625

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